Sequentially estimating the dynamic contact angle of sessile saliva droplets in view of SARS-CoV-2

TL;DR

This paper introduces a sequential confidence interval method for estimating the dynamic contact angle of saliva droplets infected with SARS-CoV-2, improving efficiency and reducing costs compared to previous models.

Contribution

It extends prior work by applying a new wrapped-exponential model and sequential estimation to better analyze saliva droplet contact angles.

Findings

Reduced data collection time and cost

Effective modeling of saliva droplet contact angles

Potential implications for understanding virus transmission

Abstract

Estimating the contact angle of a virus infected saliva droplet is seen to be an important area of research as it presents an idea about the drying time of the respective droplet and in turn of the growth of the underlying pandemic. In this paper we extend the data presented by Balusamy, Banerjee and Sahu [Lifetime of sessile saliva droplets in the context of SARS-CoV-2, Int. J. Heat Mass Transf. 123, 105178 (2021)], where the contact angles are fitted using a newly proposed half-circular wrapped-exponential model, and a sequential confidence interval estimation approach is established which largely reduces both time and cost with regards to data collection.